Effect of preterm birth on neonatal, infant, child, young adult and adult mortality- a systematic review and meta-analysis
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Nandini Shashikant Malshe
,
Anuva Kapoor
,
Kalyani P. Deshmukh
,
Chanchal Goyal
and
Aravind P. Gandhi
Abstract
Objectives
Preterm birth is associated with a higher risk of mortality. In 2020, the global incidence of preterm births was reported at 9.9 per 100 live births. This meta-analysis was undertaken to evaluate the effect of preterm birth on mortality among various age groups.
Methods
A thorough search was done on four electronic databases: “PubMed, Scopus, Web of Science, and Embase”. Adhering to PRISMA 2020 guidelines, observational analytical studies published till 4th December 2024 were included. Screening of the studies was done by two independent reviewers in two stages: title/abstract, followed by full text review of the advanced articles. It was followed by data extraction. Study quality was assessed with the Newcastle Ottawa Scale. Meta-analysis using a random-effects model was done in R Studio. PROSPERO ID: CRD42024622282.
Results
Database search yielded 1775 unique studies. 23 studies met the final predefined eligibility criteria. Preterm babies showed an increased risk of mortality compared to term babies with a pooled relative risk of 6.12 (95 % CI: 3.16–11.84) for neonatal mortality, 11.84 (95 % CI: 6.88–20.37) for infant mortality and 1.88 (95 % CI: 1.24–2.83) for 1–5 year. However, it was similar in adult mortality with a pooled relative risk of 1.21 (95 % CI: 0.07–20.12).
Conclusions
Preterm birth is strongly associated with increased risks of childhood mortality, especially in extreme and very preterm infants, but the risk persists even for late preterms.
Introduction
Babies born before 37 weeks of gestation are termed preterm. Globally, the incidence of preterm births stood at 9.9 % in 2020 [1]. A substantial global variation in preterm birth rates, ranging from 10 to 30 % across regions, have been reported by the World Health Organization reflecting differences in socioeconomic conditions, healthcare access, and data reporting systems [2]. Numerous sociodemographic factors, including maternal age, education, infant gender, and birth weight, raise the risk of mortality and morbidity in preterm babies [3]. Subsequently, preterm birth is a significant risk factor for higher mortality in the neonatal, infant, and early childhood period. Premature newborn survival is increasing due to improvements in maternal care, such as antenatal steroids, antenatal magnesium sulphate, advanced neonatal care like surfactant therapy, early enteral nutrition, and advancements in neonatal surgery. These improvements increase the survival of premature neonates into adulthood (age>18 years). Survivors face elevated cardiometabolic risks like diabetes and hypertension. Prevention and treatment of non-communicable diseases leading to premature mortality is one of the targets of the Sustainable Development Goals, and to achieve this, follow-up of premature babies into adulthood and their impact on adult mortality is important.
A 2009 population-based cohort study that included preterm neonates between 33 and 36 weeks gestational age showed a declining relative risk of mortality from 11.4 (mortality in less than 1 day old) to 3.5 (mortality in less than 1 year old) [4]. Similar findings were also found in a Bangladesh cohort research study, which found that the likelihood of death for both term and preterm neonates is highest on day one and falls by day 28 [5]. According to a Canadian population-based cohort research study, the relative risk of short- and long-term mortality from preterm birth declines from infancy (11.61) to early childhood (2.79), with the lowest risk occurring among those aged 18 to 28 (1.13) [6].
Studies have explored links between preterm birth and early-life mortality. However, since adult mortality necessitates a substantial cohort follow-up, there is a lacunae in studies which look at this relationship. A systematic review of two databases by Crump et al. in 2019 reported a significant increase in the adult mortality rates among preterm births [7]. A pooled estimate and risk of bias assessment of the included studies could not be found. Our preliminary search found no recent comprehensive Systematic Review and Meta-Analysis (SRMA) on preterm birth and mortality across age groups.
Materials and methods
We adhered to the “Preferred Reporting Items for Systematic Reviews and Meta-analyses” (PRISMA) 2020 guidelines for this SRMA and carried out an SRMA of cohort and observational studies. The study protocol was prospectively registered in the PROSPERO (ID: CRD42024622282).
Eligibility criteria
The research question addressed by this SRMA was- “What is the effect of preterm birth on neonatal, infant, child and adult mortality?” Cohort and case-control studies were included. English-language original studies were included regardless of location. All the live births of any sex were included, with the exposure being preterm birth and the comparator being term births. Outcomes included mortality at any age group.
Search strategy
A thorough search was done using an elaborate search strategy in the four major electronic databases: “PubMed, Scopus, Web of Science, and Embase”. All studies till 4th December 2024 were included. A detailed search strategy has been given in Table S1. English studies done on human participants were included. To ensure a comprehensive review, reference lists of the included studies were manually examined to identify any additional relevant studies.
Study selection process
Study selection involved three stages. Two independent reviewers (NM and AK) screened titles and abstracts, followed by full-text evaluation using predefined criteria. Disagreements were resolved through discussion and consensus with a third reviewer (APG).
Data extraction process
Data from the studies which were included based on consensus, were extracted. Two independent reviewers (NM and AK) extracted the data, and a final consensus sheet was used for analysis and review purposes. All the relevant information (baseline characters such as study identifiers, design, sample size, preterm type and outcomes) of the included studies was extracted in a pre-designed and structured MS Excel sheet.
Risk of bias assessment
Two reviewers (NM and AK) independently assessed the quality of the included studies. “Newcastle Ottawa Scale (NOS)” was used for assessing the risk of bias in all the cohort studies meeting the inclusion criteria [8]. Consensus was achieved after discussion with the third reviewer (APG).
Statistical analysis
A “random-effects model (REM)” was used to compute pooled estimates for outcomes with maximum likelihood estimators. I2 statistic was used for quantifying inter-study heterogeneity. Significant heterogeneity prompted the calculation of prediction intervals [9]. Publication bias assessment was done by Doi plots and the LFK index. Statistical evaluations were carried out using R Studio, following established coding procedures [10].
As this study is a systematic review of published data, institutional review board approval was not required.
Results
Study selection
The rigorous search on four databases yielded 1775 unique studies after removing 1,121 duplicates [ (Embase (n=333), PubMed (n=629), Web of Science (n=773), Scopus (n=1,141)] and eight studies were retrieved from other sources (citation searching). Based on predefined criteria, 125 studies were reviewed in full, of which 23 met eligibility for inclusion in the systematic review (Figure 1: PRISMA flowchart for study selection).
PRISMA flowchart of study selection.
Study characteristics
Table 1 presents the demographic characteristics of the individual studies. 23 studies met the inclusion criteria for a systematic review, and 21 studies for meta-analysis. Of these, 977,084 were preterm infants, comprising the exposed group (E), while 17,275,025 were term infants and formed the control group (C). The sample sizes across the studies varied considerably, ranging from 200 to 342,580 infants in the exposed group and from 200 to 4,655,980 infants in the control group.
Characteristics of the included studies.
| Sr. No. | Study | Country | Study design | Sample size | Preterm group size | Term group size | Mortality outcomes Reported |
|---|---|---|---|---|---|---|---|
| 1 | Crump et al. (2019) | Sweden | Cohort | 4,296,814 | 212,300 | 4,084,514 | NMR, IMR, 1–5 year mortality |
| 2 | Younes et al. (2021) | Qatar | Retrospective population based study | 15,865 | 1,389 | 14,476 | NMR |
| 3 | Gupta et al. (2017) | India | Prospective cohort study | 400 | 200 | 200 | IMR |
| 4 | Silvia et al. (2017) | France | Population-based retrospective cohort study | 696,698 | 32,856 | 663,615 | NMR, IMR |
| 5 | Femitha et al. (2012) | India | Prospective cohort study | 500 | 250 | 250 | NMR |
| 6 | Tsai et al. (2012) | Taiwan | Retrospective cohort | 7,998 | 1,491 | 6,507 | |
| 7 | Srinivasjois et al. (2017) | Australia | Retrospective cohort | 722,399 | 45,080 | 677,391 | NMR, IMR, 1–5 year mortality |
| 8 | Crump et al. (2011) | Sweden | Population-based cohort study | 674,820 | 27,979 | 626,723 | NMR, IMR, 1–5 year mortality |
| 9 | Gamini et al. (2021) | India | Prospective observational cohort | 400 | 200 | 200 | NMR |
| 10 | Razzaque et al. (2024) | Bangladesh | Cohort | 6,989 | 1,516 | 5,473 | NMR |
| 11 | Kitsommart et al. (2009) | Canada | Retrospective chart review | 9,859 | 1,193 | 8,666 | NMR |
| 12 | Khashu M et al. (2009) | Canada | Population-based cohort | 95,248 | 6,381 | 88,867 | NMR, IMR |
| 13 | Ahmed et al. (2024) | Canada | Cohort study | 4,998,560 | 342,580 | 4,655,980 | NMR, IMR, 1–5 year mortality |
| 14 | Crump et al. (2013) | Sweden | Cohort | 679,981 | 29,456 | 650,525 | NMR, IMR, 1–5 year mortality |
| 15 | Jang et al. (2020) | South Korea | Retrospective cohort | 1,422,913 | 86,068 | 1,336,845 | NMR, IMR |
| 16 | Barros et al. (2012) | Brazil | Cohort study | 15,777 | 2,366 | 12,152 | NMR, IMR, 1–5 year mortality |
| 17 | D’Onofrio et al. (2013) | Sweden | population-based cohort study | 33,00,708 | 154,322 | 3,146,386 | Mortality, Psychiatric morbidity, Academic problems |
| 18 | Juárez et al. (2016) | Sweden | Cohort multigenerational study | 12,564 | 997 | 9,347 | All-cause mortality |
| 19 | Risnes et al. (2016) | Norway | prospective observational | 1,562,647 | 19,597 | 1,265,248 | All-cause mortality |
| 20 | Koupil et al. (2005) | Sweden | Cohort | 14,193 | 250 | 554 | Death due to CVD |
| 21 | Welaga et al. (2013) | Ghana | Population-based cohort study | 17,751 | 5,675 | 12,076 | Neonatal Mortality |
| 22 | Gonzalez et al. (2015) | Chile | Descriptive analysis | 2,900,000 | 5.6/1,000 live births | NMR, IMR | |
| 23 | Mokuolu et al. (2022) | Nigeria | Prospective observational study | 14,760 | 4,938 | 9,030 | NMR |
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NMR, neonatal mortality rate; IMR, infant mortality rate; CVD, cerebrovascular diseases.
23 studies providing comprehensive data on neonatal mortality rate (NMR), infant mortality rate (IMR), and mortality in various age groups, among preterm-born children compared to their term-born counterparts, were included. The studies spanned diverse regions, six of the included studies were from Sweden [11], [12], [13], [14], [15], [16], three from Canada [4], 6], 17], one from Qatar [18], three from India [19], [20], [21], and one study each from France [22], Taiwan [23], Australia [3], Bangladesh [5], Brazil [24], South Korea [25], Norway [26], Ghana [27], Chile [28] and Nigeria [29]. Study designs included prospective, retrospective, and population-based cohorts. Gestational age classifications for preterm birth were uniformly applied across studies, allowing subgroup comparison: extreme preterm (<28 weeks), very preterm (28–31+6 weeks), moderate preterm (32–33+6 weeks), and late preterm (34–36+6 weeks), each compared against term births (≥37 weeks). Results were systematically structured into four outcomes: Neonatal Mortality Rate (NMR), Infant Mortality Rate (IMR), mortality in the age range of 1–5 years, and adult mortality, stratified clearly by gestational age subgroup (Table 2).
Summary mortality risk estimates of preterm vs. term babies.
| Outcome | No of studies | Pooled RR | 95 % CI | I2 | p-Value of I2 |
|---|---|---|---|---|---|
| Neonatal mortality rate | |||||
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| Any preterm vs. term | 14 | 6.12 | 3.16; 11.84 | 99.9 % | 0 |
| Extreme preterm vs. term | 2 | 143.14 | 120.35; 170.24 | 0.0 % | 0.4636 |
| Very preterm vs. term | 3 | 11.67 | 0.22; 610.53 | 98.1 % | <0.0001 |
| Moderate preterm vs. term | 6 | 9.19 | 2.39; 35.31 | 99.2 % | <0.0001 |
| Late term vs. term | 11 | 4.14 | 2.49; 6.90 | 94.3 % | <0.0001 |
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| Infant mortality rate | |||||
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| Any preterm vs. term | 9 | 11.84 | 6.88; 20.37 | 98.6 % | <0.0001 |
| Extreme preterm vs. Term | 4 | 112.42 | 48.84; 258.80 | 99.3 % | <0.0001 |
| Very preterm vs. term | 3 | 39.49 | 16.70; 93.42 | 99.5 % | <0.0001 |
| Moderate preterm vs. term | 4 | 13.71 | 5.13; 36.62 | 99.1 % | <0.0001 |
| Late preterm vs. term | 8 | 4.73 | 3.27; 6.85 | 98 % | <0.0001 |
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| 1–5-year mortality rate | |||||
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| Any preterm vs. term | 5 | 1.88 | 1.24; 2.83 | 93.9 % | <0.0001 |
| Extreme preterm vs. term | 3 | 1.88 | 0.33; 10.76 | 63.2 % | 0.0658 |
| Very preterm vs. term | 2 | 1.74 | 1.43; 2.12 | 0 % | 0.8866 |
| Moderate preterm vs. term | 2 | 1.92 | 1.00;3.70 | 0.0 % | 0.4560 |
| Late preterm vs. term | 3 | 2.87 | 0.72; 11.43 | 99.6 % | <0.0001 |
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| Adult mortality | |||||
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| Any preterm vs. term | 2 | 1.21 | 0.07; 20.12 | 96.1 % | <0.0001 |
| Extreme preterm vs. term | 2 | 0.99 | 0.64; 1.53 | 0.0 % | 0.7058 |
| Late preterm vs. term | 2 | 1.22 | 0.06; 26.35 | 96.4 % | <0.0001 |
Juárez et al. (2016) reported that low birth weight, small-for-gestational-age, and preterm births were significantly associated with higher risks of all-cause mortality, particularly during infancy and early to mid-adulthood, independent of maternal or socioeconomic confounders. The findings suggested that adverse perinatal conditions exert long-term effects on survival extending up to 44 years of age [15]. In a study by Koupil et al. (2005) it was seen that shorter gestational age increased the risk of cerebrovascular mortality, but no association was seen with ischemic heart disease. The study highlighted that individuals born after 36 weeks had significantly lower cerebrovascular mortality risk [16].
Neonatal mortality rate (NMR)
Any preterm vs. term
This meta-analysis included 14 studies to compare neonatal mortality rates between preterm and term infants (2–4,12,16–18,20,22–24,27,29). The pooled analysis showed that preterm infants had a significantly higher risk of neonatal mortality when compared to term infants, with a relative risk (RR) of 6.12 (95 % CI: 3.16–11.84) (Figure 2: Forest plot for pooled RR of NMR between preterm and term) All the included studies consistently showed increased mortality in the preterm group. The prediction interval ranged from 3.16; 11.84, with the exact magnitude may vary considerably across populations. Heterogeneity was high (I2=99.9 %), indicating substantial variability among studies. The pooled RR remained between 5.61 and 7.09 upon omitting individual studies (Figure 2) Notably, exclusion of outliers such as Mokuolu et al. (2022) or Silvia et al. (2017) did not substantially alter effect estimates or heterogeneity, supporting the stability of the findings. (Supplementary Figure 1) An LFK index of −0.92 indicates no significant asymmetry in the Doi plot, implying the absence of potential publication bias. (Supplementary Figure 2). A positive association between gestational age, foetal growth and mortality occurring due to cerebrovascular disease was reported by Koupil et al., wherein 14,193 neonates were included [16]. Also, a reduction in the occurrence of low birth weight and neonatal mortality was seen over decades by Gonzalez et al. in Chile between 1990 and 2000, which was attributable to declines in birth weight–specific and gestational age–specific mortality rates [28].
NMR pre vs. term.
Extreme preterm vs. term
The pooled analysis of two studies shows that extreme preterm infants have a significantly higher risk of neonatal mortality, with a combined RR of 143.14 (95 % CI: 120.35–170.24) [3], 14]. The total number of neonatal deaths among extreme preterm infants was 2,680 out of 11,149, compared to 9,109 out of 3,823,777 among term infants. The heterogeneity between studies was not significant (I2=0 %, p=0.4636), and the prediction interval ranged from 112.98 to 181.35. The sensitivity analysis (leave-one-out meta-analysis) confirms the robustness of the main finding. Omitting either study (D’Onofrio or Srinivasjois) results in consistent relative risks: 135.41 and 143.62, respectively. The pooled estimate remains unchanged at RR=143.14 (95 % CI: 120.35–170.24) with no heterogeneity (I2=0 %).
Very preterm vs. term
Three studies were included in this meta-analysis to compare neonatal mortality rates between very preterm and term infants [5], 18], 27]. The pooled analysis showed a markedly increased risk of neonatal death in very preterm infants, with an RR of 11.67 (95 % CI: 0.22–610.53). Individually, both studies showed an elevated mortality risk. The prediction interval (0.00; 30,434.00) was also wide, thus reflecting considerable variation in effect size. Heterogeneity was substantial (I2=98.1 %). Leave-one-out analysis was suggestive of no alterations in the direction of relative risk, albeit variations in the magnitude.
Moderate preterm vs. term
Six studies were included in this meta-analysis to compare neonatal mortality between moderate preterm and term infants [3], 5], 14], 18], 22], 27]. The pooled analysis showed that moderate preterm infants had a significantly higher risk of neonatal death compared to term infants [RR of 9.19 (95 % CI: 2.39–35.31)]. All the included studies demonstrated an increased mortality risk in the preterm group. The 95 % prediction interval ranged from 0.27 to 309.95. Substantial heterogeneity was observed (I2=99.2 %). Therefore, these findings indicate a substantially increased but variable risk of neonatal mortality among moderate preterm infants. Omission of any study resulted in RRs from 9.19 [0.76–111.65] to 18.09 [3.62–90.39], with I2 consistently>91 %, indicating robustness of the estimate.
Late preterm vs. term
Meta-analysis of 11 studies was done for this outcome to compare the neonatal mortality rate between late preterm and term infants [3], [4], [5, 14], 17], 18], [20], [21], [22], [23], [24]. Pooled analysis showed a significantly higher risk of neonatal death was seen in the late preterms when compared to term infants, with a relative risk of 4.14 (95 % CI: 2.49–6.90). All the studies included in this meta-analysis demonstrated increased mortality risk in the preterm group. The 95 % prediction interval ranged from 1.23 to 18.40. However, substantial heterogeneity was observed (I2=94.3 %). Thus, these findings indicate that there is an increased risk of mortality in late preterm neonates across diverse geographical regions and healthcare settings. Sequential removal of individual studies yielded pooled RRs between 4.34 and 5.63, and I2 remained>84 % in all iterations. No single study altered the overall direction or statistical significance of the effect. For the comparison between late preterm and term births, the LFK index was −3.07, indicating evidence of asymmetry and potential publication bias.
Infant mortality rate (IMR)
Any preterm vs. term
Ten studies were included (2,3,5,10–12,18, 21, 23,24). The pooled RR for IMR was 11.84 (95 % CI: 6.88–20.37), with a prediction interval of 2.03–69.12, indicating significantly higher mortality in preterm births. Heterogeneity was high (I2=98.6 %), based on 30,169 preterm and 32,096 term deaths. Leave-one-out analysis showed consistently significant RRs (10.19–13.16). The Doi plot (LFK index −4.42) indicated asymmetry, suggesting publication bias.
Extreme preterm vs. term
Four studies reported on extreme preterm births (<28 weeks) [3], 6], 12], 14]. The pooled analysis found an increased risk of infant death in extreme preterm infants, with an RR of 112.42 (95 % CI: 48.84–258.80). All three studies showed consistently high and statistically significant effect sizes, indicating substantially higher mortality among infants born extremely preterm. The prediction interval ranges from 17.47 to 723.38. Heterogeneity was very high (I2=99.3 %).
Very preterm vs. term
Crump et al. (2019), Ahmed et al. (2024) and D’onofrio et al. (2013) contributed to this meta-analysis [6], 12], 14]. The pooled analysis showed that very preterm infants had a markedly higher risk of dying in the first year of life, with an RR of 39.49 (95 % CI: 16.70–93.42). The studies individually demonstrated a substantial and statistically significant increase in risk compared to term births. The prediction interval ranged from 7.08 to 220.33. While heterogeneity was present (I2=99.5 %), the direction of effect was consistent across studies.
Moderate preterm vs. term
The pooled analysis of the four studies found that moderate preterm infants had a significantly higher risk of infant death, with an RR of 13.71 (95 % CI: 5.13; 36.62) [3], 6], 14], 22]. All four studies showed a clear elevation in risk, with effect estimates consistently favouring lower mortality in term infants. The prediction interval ranged from 1.55 to 121.17. There was substantial heterogeneity (I2=99.1 %).
Late preterm vs. term
Eight studies were included in this meta-analysis to compare infant mortality between late preterm and term births [3], 4], 6], 12], 14], 19], 22], 24]. The pooled analysis showed that late preterm infants had a significantly higher risk of dying in infancy compared to term infants, with an RR of 4.73 (95 % CI: 3.27–6.85). All but one study showed a statistically significant increase in mortality. The 95 % prediction interval ranged from 1.67 to 13.37. Heterogeneity was substantial (I2=98.0 %).
Seven studies reported explicitly that they have included preterm births through caesarean section, and the proportions were higher in the preterm groups compared to term group. However, Srinivasjois et al. reported that even after adjusting for the mode of delivery, neonatal and post-neonatal (till 1 year of age) mortality was significantly higher in the preterm groups than the term group [3]. Razzaque et al. also reported similar findings in the neonatal mortality after adjusting the mode of delivery [5].
1–5 Year mortality rate
Any preterm vs. term
Meta-analysis of five studies (2,11, 12, 14,24) showed significantly higher 1–5 year mortality in preterm children (RR: 1.88; 95 % CI: 1.24–2.83; I2=93.9 %). While effect sizes varied, all studies indicated elevated risk. The stable leave-one-out results confirmed this association. An LFK index of 1.31 suggested potential publication bias.
Extreme preterm vs. term
Three studies (2,11,14) suggested elevated 1–5 year mortality in extremely preterm children (RR: 1.88; 95 % CI: 0.33–10.76), though the wide CI and prediction interval (0.09–39.27) indicate substantial uncertainty due to few events. Heterogeneity was moderate (I2=63.2 %).
Very preterm vs. term
The pooled RR across the two studies reporting this outcome is 1.74 [1.43, 2.12], indicating a 74 % increased risk of mortality between ages 1 and 5 for very preterm births compared to term births [13], 14]. Heterogeneity was low (I2=0.0 %), suggesting no significant variability between studies. The prediction interval is wide, ranging from 0.44 to 6.86. The leave-one-out analysis was suggestive of a strong relation between very preterm birth and mortality in 1–5 year of age, as the pooled relative risk remains unaltered on omitting either of the studies.
Moderate preterm vs. term
The combined RR of the two included studies is 1.92 [1.00, 3.70]. (2, 12) I2=0.0 % suggests no heterogeneity, and the prediction interval ranges from 0.80 to 4.63. It was evident in the leave-one-out sensitivity analysis that omission of either of the studies did not alter the pooled relative risk.
Late preterm vs. term
Three studies evaluated 1–5 year mortality in late preterm vs. term infants [4], 6], 14]. The pooled analysis did not show significantly higher risk of death between ages 1 and 5 among late preterm children, with an RR of 2.87 (95 % CI: 0.72–11.43). The prediction interval ranged from 0.19 to 43.75. Notably, heterogeneity was high (I2=99.6 %).
Adult mortality
Any preterm vs. term
The pooled relative risk of the two studies was 1.21 (95 % CI: 0.07; 20.12), with no significant association. This estimate also had substantial heterogeneity (I2=99.3 %, p<0.0001), and the prediction interval was notably wide (0.01–147.73) [12], 26].
Extreme preterm vs. term
The pooled relative risk of the two studies reporting the outcome was 0.99 (95 %CI:0.64; 1.53), showing no association. It had a heterogeneity of 99.5 % with a prediction interval of 0.06; 12.50 [12], 26].
Late preterm vs. term
A pooled relative risk of 1.22 (95 %CI:0.06; 26.35) was reported by the two studies for the outcome [12], 26]. However, no significant association was seen with the outcome variable. A substantial heterogeneity of 99.5 % with a prediction interval of 0.06; 12.50 was shown by the studies.
Quality assessment
Risk of bias was assessed using the Newcastle Ottawa Scale. Gonzalez et al. ([27]) was rated fair, while Jang et al. ([24]) and Kitsommart et al. ([16]) were rated poor. All other studies were graded as good quality (Table S2).
Discussion
This review analysed mortality due to prematurity across 23 studies, including registries from Australia, Sweden, and databases like the French Medico-administrative and Perinatal registries. These sources offer robust, long-term follow-up. The meta-analysis showed a strong association between preterm birth and mortality at all life stages – neonatal, infant, and 1–5 years – except adulthood. Desta M et al. [30] in an SRMA of the effect of preterm birth on risk of adverse perinatal and neonatal outcomes also showed an increased risk of neonatal mortality in preterm babies. A significantly higher rates of neonatal complications are seen amongst the late preterm infants (those born between 34 and 36 weeks of gestation) than the full-term infants. These complications include respiratory distress syndrome (RDS), sleep apnea, necrotising enterocolitis (NEC), and intraventricular haemorrhage (IVH) [31], 32] Late preterm children not only have increased mortality and in-hospital morbidity, but also later in life, they are more likely to suffer from long-term motor and cognitive impairments, chronic disease and premature death [13], 33], 34].
Early childhood mortality (neonatal and infant) was strongly associated with preterm birth (RR>6). A dose-response pattern showed shorter gestation linked to higher early childhood mortality. Each additional week of gestation showed an improvement in the survival rates of preterm infants in the past [35] signifying the importance of prolonging the gestation as far as possible to term.
The elevated risk of infant mortality persisted even after adjusting for socioeconomic and perinatal covariates, as reported in another study by Crump et al. [7]. They found preterm birth was independently associated with higher all-cause mortality between ages 6–30, consistent across gestational categories, supporting long-term vulnerability. Preterm birth is also linked to congenital anomalies and endocrine, respiratory, and cardiovascular disorders in young adulthood.
It can also lead to various other diseases like asthma, hypertension, diabetes and diseases related to the thyroid and its functions [7], 26], 36]. Cardiovascular disorders were reportedly more common in individuals born preterm [37], 38]. This can be associated with the increase in risk due to maternal near miss owing to hypertension and haemorrhage, which leads to reduced blood supply to the foetus, resulting in perinatal mortality or preterm delivery [30].
Koupil et al. [16] focused on exploring the relationship between gestational length and mortality due to cerebrovascular diseases. Using a cohort of 14,193 individuals born in Uppsala between 1915 and 1929, the study examined how fetal growth rate and gestational duration were linked to the risk of death from ischemic heart disease (IHD) and cerebrovascular disease. The findings indicated that a shorter gestational period was related to a higher risk of mortality from cerebrovascular disease, while no such association was found with IHD. Additionally, the risk of mortality following an occlusive stroke was lower among individuals born at 36 weeks of gestation or later. The pooled estimates were consistent with those reported by Ahmed et al. [6] who analysed national birth cohort data from Canada (1983–2019) and found that individuals born preterm had higher all-cause mortality in adulthood (>18 years) compared to their term-born peers.
Crump et al., in 2011 and 2013, conducted a population-based cohort study and reported 10,392 deaths between the ages of 0 and 45 years among individuals born preterm (<37 weeks of gestation) [27], 37]. Age-stratified mortality counts indicated 390 deaths in the 10–19 year age group, 591 deaths in the 20–29 year group, and 319 deaths in the 30–45 year group, suggesting a sustained mortality burden extending into mid-adulthood. Crump et al. [7] in their systematic review on preterm birth and adult mortality, reported a significant association between them. Also, these findings remained consistent regardless of sociodemographic, perinatal, and maternal factors (all studies), and were not explained by unmeasured shared familial factors in co-sibling analyses (conducted in four studies). Confounders such as the cardiovascular and metabolic factors might have also distorted association between the preterm and adult mortality in these studies. Thus, an adjusted analysis incorporating these factors must be undertaken in the future studies. However, in our SRMA, the adult mortality rate (20–29 years) among preterm and term individuals appeared similar, which may be attributed to the limited number of studies reporting this specific outcome. (26,11).
Srinivasjois et al. [3] and Razzaque et al. [5] indicated no effect of cesarean sections on the association between preterm and childhood mortality. In line with this, most of the studies among preterm deliveries in the past also reported that cesarean section did not increase the risk of perinatal mortality. The above findings can be attributed to the appropriate selection of the preterm deliveries (medically indicated preterm deliveries) for elective cesarean section, since they might not withstand the stress of the vaginal births [39]. In this regard, it is vital to adhere to the existing guidelines, on when not to prolong the pregnancy (medically indicated preterm deliveries) and ensure preterm deliveries to reduce perinatal morbidity and mortality [40].
Strengths of our study are the inclusion of major databases, which ensured pooling of studies across the globe and from countries with large live birth cohorts for analysis. Severity-wise risk ratio for preterm births could be calculated for mortality risk and compared with term gestational age. However, there is a smaller number of studies reporting the association between preterm birth and adult mortality, which were eligible for meta-analysis. We were able to pool data from only two studies, highlighting the need for more research with extensive and long-term follow-up in the future. Limited studies were from low and low-middle-income countries, which disproportionately face the public health problem of preterm birth. A substantial heterogeneity between the studies was observed, which might be due to differences in study design, populations, outcomes, and follow-up durations.
Conclusions
Overall, it can therefore be inferred that preterm birth is strongly associated with significantly increased risks of childhood mortality. The risk is highest in extreme and very preterm infants. However an increased mortality rate was also observed among late preterm infants (34–36 weeks). This finding emphasizes the need to recognize late preterm also as a vulnerable group, and there should be targeted perinatal and postnatal care for this population, to reduce the childhood mortality. Although steps need to be taken to reduce the pre-term deliveries as much as possible, it is also equally essential to ensure medically indicated preterm deliveries (especially the cesarean sections) are done are as per the standard guidelines. In such scenarios, effective post-delivery management should be done to ensure the survival of the child during neonatal period and infancy. All studies in the future may also undertake analysis by adjusting for the mode of delivery while ascertaining the association between preterm and mortality.
Acknowledgments
The authors would like to thank the contribution of the Department of Health Research supported SARANSH-1 (Systematic Reviews And Networking Support in Health) workshop organised by the Department of Community Medicine, All India Institute of Medical Sciences, Nagpur, India and the Technical Resource Centre (Centre for Evidence Based Guidelines), Department of Community Medicine, AIIMS Nagpur for developing their capacity to undertake the systematic review.
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission. Nandini Malshe: Data curation; Formal analysis; Methodology; Roles/Writing – original draft. Anuva Kapoor: Data curation; Formal analysis; Validation; Methodology; Writing – original draft, review & editing. Kalyani P Deshmukh: Data curation; Formal analysis; Methodology; Visualization; Roles/Writing - original draft. Chanchal Goyal: Data curation; Formal analysis; Methodology; Visualization; Roles/Writing – review and editing. Aravind P Gandhi: Conceptualization; Data curation; Methodology; Project administration; Resources; Writing – review & editing.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: The authors state no conflict of interest.
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Research funding: None declared.
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Data availability: All data used are provided in the manuscript and the supplementary files.
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